ArticleInternational journal of molecular sciences2023
A Comprehensive and Integrative Approach to MeCP2 Disease Transcriptomics.
Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Variable expression ofProceedings of the National Academy of Sciences of the United States of America · 2024Pooled it
- Spatially resolved mapping of histones reveals selective neuronal response in Rett syndrome.The FEBS journal · 2026Article
- Single-nucleus profiling reveals a core disease signature and cell type-specific vulnerabilities in early Rett syndrome.Science advances · 2026Article
- Early postnatal DNA methylation dynamics define neuronal subtypes and are disrupted by MECP2 loss.bioRxiv : the preprint server for biology · 2026Article
- Transcriptomic data and biomedical literature synergize in finding pharmacologic gene regulators.bioRxiv : the preprint server for biology · 2026Article
- MeCP2 functions as a DNA methylation reader in immune homeostasis and cancer.Frontiers in epigenetics and epigenomics · 2026Review
- MeCP2 and non-CG DNA methylation stabilize the expression of long genes that distinguish closely related neuron types.Nature neuroscience · 2025Article
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- Modeling antisense oligonucleotide therapy in MECP2 duplication syndrome human iPSC-derived neurons reveals gene expression programs responsive to MeCP2 levels.Human molecular genetics · 2024Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
Mutations in MeCP2 result in a crippling neurological disease, but we lack a lucid picture of MeCP2's molecular role. Individual transcriptomic studies yield inconsistent differentially expressed genes. To overcome these issues, we demonstrate a methodology to analyze all modern public data. We obtained relevant raw public transcriptomic data from GEO and ENA, then homogeneously processed it (QC, alignment to reference, differential expression analysis). We present a web portal to interactively access the mouse data, and we discovered a commonly perturbed core set of genes that transcends the limitations of any individual study. We then found functionally distinct, consistently up- and downregulated subsets within these genes and some bias to their location. We present this common core of genes as well as focused cores for up, down, cell fraction models, and some tissues. We observed enrichment for this mouse core in other species MeCP2 models and observed overlap with ASD models. By integrating and examining transcriptomic data at scale, we have uncovered the true picture of this dysregulation. The vast scale of these data enables us to analyze signal-to-noise, evaluate a molecular signature in an unbiased manner, and demonstrate a framework for future disease focused informatics work.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.